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arXiv · 2208.04418

Incorporating testing volume into estimation of effective reproduction number dynamics

Isaac H. Goldstein·Jon Wakefield·Volodymyr M. Minin
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Abstract

Branching process inspired models are widely used to estimate the effective reproduction number -- a useful summary statistic describing an infectious disease outbreak -- using counts of new cases. Case data is a real-time indicator of changes in the reproduction number, but is challenging to work with because cases fluctuate due to factors unrelated to the number of new infections. We develop a new model that incorporates the number of diagnostic tests as a surveillance model covariate. Using simulated data and data from the SARS-CoV-2 pandemic in California, we demonstrate that incorporating tests leads to improved performance over the state-of-the-art.

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Isaac H. Goldstein, Jon Wakefield, Volodymyr M. Minin. 2022-08-08. Incorporating testing volume into estimation of effective reproduction number dynamics. https://arxiv.org/abs/2208.04418

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